Journal of Deep Learning, Computer Vision and Digital Image Processing
Vol 2 No 1 (2024): Vol. 2 No. 1 (March 2024)

Pengendalian Untuk Mengoptimalkan Produksi Mie Pada Warung Mie Pedas Dengan Menggunakan Logika Fuzzy Berbasis Metode Tsukamoto

Safitri, Ayu (Unknown)
Azzahra, Aura (Unknown)
Kurnia, Shahnaz Tasha (Unknown)



Article Info

Publish Date
30 Mar 2024

Abstract

ABSTRACT The rapid development of technology has led to a change in consumer consumption patterns, including food consumption, especially the production of noodles. Noodles are a source of energy and nutrients needed by all living organisms. One of the noodle dishes often used as a substitute for rice is instant noodles. Instant noodles are easy to serve and practical, and their production is usually carried out based on consumer demand. However, there is still a lack of research on determining the optimal production quantity of instant noodles to meet consumer demand and align with the availability of raw materials. Therefore, it is suggested to use Fuzzy Logic-based Method Tsukamoto to optimize noodle production at noodle shops. The Fuzzy Logic Method Tsukamoto helps regulate noodle production in accordance with consumer preferences and avoid waste of raw materials. The results of the study show that the method can adjust the production quantity of instant noodles based on consumer demand and availability. This approach ensures that noodle production meets consumer needs and prevents overuse of raw materials Keywords: Noodles, Tsukamoto, demand, supply, production

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Journal Info

Abbrev

DECODING

Publisher

Subject

Computer Science & IT

Description

The Journal of Deep Learning, Computer Vision and Digital Image Processing (DECODING), covers all topics of artificial intelligence and soft computing and their applications, including but not limited to: • Neural networks • Reasoning and evolution • Intelligent search • Intelligent planning ...